Monitoring of patient cardio-respiratory events is of vital clinical importance in the early detection of potentially fatal conditions. Current technologies that involve contact sensors require that the individual wears such devices constantly. Such a requirement can lead to discomfort, psychological dependence, loss of dignity, and may even cause additional medical issues such as skin infection when sensors have to be worn for an extended period of time. Elderly patients, infants, and those suffering from chronic medical conditions are more likely to suffer from such negative effects of continuous monitoring. The use of an unobtrusive, non-contact, imaging based monitoring of physiological events can go a long way towards alleviating some of these issues. Previous efforts have been directed to systems and methods which employ video image devices for monitoring a patient for a desired physiological function. In these methods, videos are captured of a region of interest of the resting patient and processed to estimate cardiac and respiratory functions from physiological signals extracted from time-series signals obtained from those videos. Xerox researchers have determined that movement by the resting patient such as turning the head, moving an arm, and the like, may impart or induce motion artifacts into the physiological signals extracted from video of that patient and thus negatively impact the accuracy of physiological signals obtained therefrom. The present application is directed to this issue.
Accordingly, what is needed in this art are sophisticated systems and methods for increasing the accuracy of physiological signals obtained from a video of a subject being monitored for a desired physiological function.